Combined use of Design of Experiment (DoE) and Process Automation for the Efficient Optimization of New Synthetic Transformations Universita’ dell’Insubria-Dipartimento.

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Presentation on theme: "Combined use of Design of Experiment (DoE) and Process Automation for the Efficient Optimization of New Synthetic Transformations Universita’ dell’Insubria-Dipartimento."— Presentation transcript:

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OFAT (One Factor at A Time) Approach OFAT results in a set of experiment in which only one factors is varied S M P AB C incomplete picture of the overall process factor interactions are not revealed number of experiments not fixed not possible to perform experiments in parallel -

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DoE (Design of Experiment) Approach S M P AB C DOE results in a set of pre-planned experiments in which factors are varied at the same time factor interactions are revealed precise estimation of factors effect 2-level Factorial Design experimental matrix mathematical model of the chemical process based on statistical analysis possibility to perform experiment in parallel

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Step 2. Planning the Experiment: Statement of the Problem State experimental objectives: which type of design? Process screening Process optimization Process robustness testing which variables are most influential? how variables are relevant? Do small changes in uncontrolled variables influence the response?

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Step 2. Planning the Experiment: Full vs. Fractional Factorial Designs n o of factors n o of experiments Fractional Factorials exploit the redundancy of Full Factorials to reduce the n o of exps 7 factors can also be studied in only a fraction of the original full factorial design. Full Fractional

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Step 3. Performing the Experiment Use randomization to reduce the influence of nuisance factors If possible, operate in parallel since we rely on a previous experimental plan Monitor and record values of uncontrolled factors Perform a scoping study: check -- - vs. +++ and reproducibility.

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Different options when the linear model is not adequate. Many are extensions of the 2-level factorial design 2-level FD CCDCCF3-level FD Factor levels 533 Number of Experiments Geometries of the Explored Space sphericalcubic Characteristics: Box-Behnken spherical Response Surface Modelling (RSM): an Overview

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Summary and Conclusions A mathematical regression model is generated. This model is empirical and valid only within the studied factor range. A better understanding and control of the process are gained by interacting with the model. Use of non-statistical knowledge of the problem for choosing factors and their levels, interpreting the results... “ Using statistics is no substitute for thinking about the problem.” Design and analysis of Experiments D.C. Montgomery DOE results in a set of experiments in which factors are varied at the same time in an organized and systematic approach

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Suggestion If you find DoE applied to boring chemistry problem ….. Using DoE to Spend Less Time in The Traffic Screening Ingredients (for Homemade Bread) Most Efficiently with Two- Level Design of Experiment Applied DoE to Microwave Popcorn and more and more…. By Mark J. Anderson, consultant, Stat-Ease, Inc., Minneapolis, MN